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Maritime Park Journal of Maritime Technology and Society
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Transforming the Shipping Industry with Autonomous Ships and Artificial Intelligence

Authors: Muhammad Riyadh;

Transforming the Shipping Industry with Autonomous Ships and Artificial Intelligence

Abstract

The shipping industry has long been a critical component of global trade and commerce, but it has faced numerous challenges, including labor shortages, safety concerns, and the need to reduce environmental impact. In recent years, the emergence of autonomous ships and the application of artificial intelligence (AI) have the potential to transform the shipping industry, addressing these challenges and driving innovation. This study explores the role of autonomous ships and AI in revolutionizing the shipping industry. It employs a multifaceted research approach, including a comprehensive literature review, expert interviews, case studies, and quantitative analysis, to provide a detailed understanding of the key developments, potential benefits, and challenges associated with the integration of these technologies. The research findings reveal significant advancements in autonomous ship technology, with vessels equipped with advanced sensors, navigation systems, and decision-making algorithms that enable them to operate with minimal to no human intervention. The integration of AI further enhances the capabilities of autonomous ships, enabling them to process vast amounts of data, optimize routes and energy usage, and improve overall safety and reliability. The study identifies the potential benefits of autonomous ships and AI-powered shipping operations, including increased efficiency, improved safety, reduced operational costs, and decreased environmental impact. However, it also highlights the challenges that must be addressed, such as the need for regulatory adaptations, overcoming technological limitations, managing cybersecurity risks, and addressing public acceptance.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
hybrid